1. Field of the Invention
The present invention relates to a parts recognition data preparing method and a preparing device and an electronic parts mounting device and a recording medium, which are applied to a device that recognizes an electronic parts based on image data being obtained by picking up an image of the electronic parts to prepare parts recognition data that record recognition conditions of the electronic parts, and relates to the data inputting technology that is useful for recognizing the electronic parts, which is sucked onto a suction nozzle of the electronic parts mounting device, to correct its mounting position based on its suction attitude, for example.
2. Description of the Related Art
In recent years, in the electronic parts mounting field, the technology for mounting the electronic parts on the circuit board at high speed with high precision is required. Normally the image recognizing technology for executing the correct of a mounting position and an amount of rotation of the electronic parts by processing image data, which are obtained by picking up the image of the electronic parts, at high speed to detect a position and an amount of rotation of the electronic parts precisely is employed. Also, with the progress of multi-electrodes and miniaturization of the electronic parts, the technology for detecting and correcting the electrode position tends to be employed such that individual electrodes of the electronic parts can be mounted on lands of the substrate precisely. In order to detect individual electrode positions, it must be made clear as the premise condition in which way individual electrode are arranged. Therefore, not only the algorithm of detecting the electrodes must be decided in response to the shape of the parts, but also data such as necessary dimensions, number of electrodes, etc. must be set in response to this algorithm.
First, a behavior of preparing the data when a square-shaped chip parts is recognized will be explained hereunder. FIG. 48 is a view showing an external appearance of a square-shaped chip parts 301. The square-shaped chip parts 301 has a shape in which electrodes 302 are arranged on its right and left sides. When the parts which has the electrodes 302 on its right and left sides is to be recognized, detection of the electrodes 302 is carried out by using the algorithm for the square-shaped chip parts. In this algorithm, as shown in FIG. 48, data of the square-shaped chip parts 301 of parts dimensions L1, W1 and electrode lengths d1, d2 are needed. As a result, parts recognition data to recognize the square-shaped chip parts 301 need    parts dimensions horizontal: L1    vertical: W1    electrode lengths length 1: d1    length 2: d2.
Next, a behavior of preparing the data when a QFP parts is recognized will be explained hereunder. FIG. 49 is a view showing an external appearance of a QFP parts 311. The QFP parts 311 has a shape in which electrodes 312 that are aligned at an equal interval are arranged on upper/lower/left/right sides respectively. In case such parts on the upper/lower/left/right sides of which the electrodes 312 are arranged at an equal interval is to be recognized, detection of the electrodes 312 is executed by using the algorithm for the lead-type parts. In this algorithm, as shown in FIG. 49, data of the QFP parts 311 about parts dimensions L1, W1, lead outer shapes Lt, Wt, a width of the electrode h1, an interval between the electrodes Pt, and the number of the electrodes Nu, Nd, Nl, Nr are required. As a result, parts recognition data to recognize the square-shaped chip parts 301 need    parts dimensions horizontal: L1    vertical: W1    lead outer shapes horizontal: Lt    vertical: Wt    electrode dimensions width 1: h1    interval: Pt    number of the electrodes upper: Nu    lower: Nd    left: Nl    right: Nr.
In this manner, the necessary parts recognition data are different according to the used algorithm. However, if data about    parts dimensions: L1, L2, W1, W2    lead outer shapes: Lt, Wt    electrode dimensions: d1, d2, h1, h2, Pt    number of the electrodes: Nu, Nd, Nl, Nr
and others are employed as input definitions of the dimensions, all parts shapes can be represented.
Also, the parts recognition data contain camera numbers Cn for switching the visual field size of the camera to pick up the image, illumination code numbers Lc for switching an illumination angle and an illumination strength when the electronic parts is illuminated, etc. in addition to the above data. These data must be set according to size, shape, etc. of the electronic parts as the recognition object.
In this manner, if fixed forms of dimensional definitions are employed, the parts recognition data of the same size can be prepared irrespective of the shape of the electronic parts.
In the related art, these parts recognition data are set entirely manually. In other words, the parts recognition data are input by comparing the electronic parts as the recognized object with the data sheet shown in FIG. 5, which is prepared every parts type, then selecting the optimum recognition algorithm, and then measuring dimensions at predetermined positions in accordance with the selected recognition algorithm.
In the above method in the related art, first it is important which one of plural prepared recognition algorithms should be selected. For example, in the case of is the connector parts 321 shown in FIG. 50, the recognition algorithm used to recognize the above QFP parts is suitable. However, if a view of the QFP parts is set forth in the data sheet that is used to select the recognition algorithm, a sufficient knowledge of the recognition algorithm is required to decide whether or not the same recognition algorithm can be applied to the connector parts in FIG. 50. Even if the optimum recognition algorithm can be selected, input data are different from the data of the QFP parts and thus the data corresponding to Lt, Nd, Nl, Nr are not present in the connector parts 321. Therefore, since there exist input items of data that are not actually present in the parts, the operator does not know how to input these data and is troubled with the inputting operation when such operator starts to input the data via the input screen shown in FIG. 51, for example.
In order to avoid such situation, it may be considered that the data sheets are prepared individually in response to the shape of the parts. In such case, not only a great deal of data sheets are needed but also it is not easy to select the appropriate data sheet from these data sheets.
Also, the connector parts 331 shown in FIG. 52 is present in the connector parts. In this connector parts 331, reinforcing electrodes 334 are arranged on both ends separately from the normal electrodes 332. In this manner, if the reinforcing electrodes 334 are provided to both ends, detection is carried out while ignoring the reinforcing electrodes 334. As a result, the parts recognition data has the completely same shape as the connector parts 321 shown in FIG. 51. However, if the operator does not know to ignore the reinforcing electrodes 334, two types of lead widths and lead intervals are present and thus the operator cannot decide how to input the data.
Such exceptional inputting method tends to increase more and more because the shapes of the parts become complicated. Therefore, a deep knowledge of the adaptive recognition algorithm is required to prepare the parts recognition data.
The present invention has been made in view of such problems in the related art, and it is an object of the present invention to provide a parts recognition data preparing method and a preparing device and an electronic parts mounting device and a recording medium, which are capable of preparing parts recognition data, which are set to respective electronic parts and are referred to when the electronic parts are to be recognized, precisely and quickly not to know particularly the characteristic of the recognition algorithm.